This paper discusses and documents the algorithms of SsfPack 2.2. SsfPack is a suite of C
routines for carrying out computations involving the statistical analysis of univariate and …

This article presents a review of some modern approaches to trend extraction for one-
dimensional time series, which is one of the major tasks of time series analysis. The trend of …

This new edition updates Durbin & Koopman's important text on the state space approach to
time series analysis. The distinguishing feature of state space time series models is that …

Modelling based on finite mixture distributions is a rapidly developing area with the range of
applications exploding. Finite mixture models are nowadays applied in such diverse areas …

The last twenty years have witnessed tremendous advances in the mathematical, statistical,
and computational tools available to applied macroeconomists. This rapidly evolving field …

A simulation smoother in state space time series analysis is a procedure for drawing
samples from the conditional distribution of state or disturbance vectors given the …

The aim of this research is to discuss the ability to forecast real crude oil price by the use of
Time-Varying Vector Autoregression (TVP-VAR) models. In particular, model averaging and …

A new approach is proposed for forecasting a time series with multiple seasonal patterns. A
state space model is developed for the series using the innovations approach which …

This paper investigates a new approach to diffuse filtering and smoothing for multivariate
state space models. The standard approach treats the observations as vectors, while our …

Gretl is an econometrics package, including a shared library, a command-line client program
and a graphical user interface. User-friendly Gretl offers an intuitive user interface; it is very …